2017.10.23 meetup Data to Text Automated Text Generation

Q1. deep learning and language models, the future in data to text, (end2end)
A1. Seq2seq looks the same, how to incorporate variety (use historic knowledge) variation, (may be use knowledge templates as constraints)
Q2. measure to optimize and measure to fluency, (BLEU is not that good)
A2.
Q3. data representation (how to deal, lacking type system or not flat table, even semi-structured) slot-based may not handle (in variety)
Q4. document planning is placed directly after content selection
Q5. sentence level scoreing and comparing
A5. human based, no possible measure available now (maybe in application)
Q6. where to find corresponding sentence data for structured data
A6. use wikipedia or some available parallel dataset (already great impact),
(MS 学术大数据, e.g. related work auto-generation)